In the case of the gyro, a specific class of gyro was identified in which the gyro bias reversed polarity when the drive and sense axes were interchanged. This particular class of gyro was identified as Class II Coriolis Vibratory Gyro and is characterized by being inherently counterbalanced, symmetrical about the input axis and having orthogonal degenerate vibration modes. Self calibration of the gyro bias is achieved by employing two gyros to measure the angular rate and sequentially reversing the gyro bias. The sequence of data from the gyros may be processed in an algorithm to solve for the gyro biases and subtract them from the measured rate. The two self-calibrated gyro angular rate measurements are averaged to reduce the angle random walk.
Self-calibration of a gyro bias under dynamic operating conditions requires the simultaneous measurement of angular rate by a pair of Class II Coriolis Vibratory Gyros (CVG) or a single gyro with dual sensing elements. Class II CVG are chosen for their ability to reverse polarity of the gyro bias by interchanging their drive and sense modes. An algorithm solves a set of four equations to estimate the gyro bias and subtract it from the measured angular rate. A Dual Resonator Gyro (DRG) may facilitate this simultaneous measurement of angular rate by a pair of gyros. System simulations have shown that the contribution of gyro bias uncertainty to the growth of position error of an inertial navigation system can be reduced by nearly three orders of magnitude using self calibration of gyro bias.
Gyro scale factor uncertainty is another source of error in inertial systems. The contribution to position error due to scale factor uncertainty is dependent on the magnitude of the angular rate experienced. Compensating for gyro scale factor uncertainty would further improve the performance of inertial navigation system.
There is a need in the art for improved methods for self-calibrating gyro scale factor.